The present disclosure relates generally to patient monitoring systems and, more particularly, to signal processing techniques for patient monitoring systems.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
In the field of medicine, doctors routinely desire to monitor certain physiological characteristics of their patients. Accordingly, a wide variety of systems and devices have been developed for monitoring many of these physiological characteristics. Generally, these patient monitoring systems provide doctors and other healthcare personnel with the information they need to provide the best possible healthcare for their patients. Consequently, such monitoring systems have become an indispensable part of modern medicine.
In general, these patient monitoring systems may include a patient sensor that has a detector (e.g., an optical or electrical detector) that is configured to perform a measurement on the tissue of a patient. However, the signal produced by the detector may suffer from various types of noise (e.g., electrical noise, interference, artifacts from patient activity, etc.). Such noise in a detector signal may introduce substantial complexity as well as possible inaccuracy into the determination of the physiological parameter of the patient. Further, the signal artifacts may be translated throughout the signal processing. As such, if a signal includes a substantial amount of noise it may be difficult to accurately calculate the physiological parameter of the patient using conventional methods.